Existing literature attempting to model the determinants of Bitcoin pricing has used a combination of economic, transactional, and technical factors as the independent variables. We seek to build on this body of knowledge by narrowing our investigation to the impact of Consumers’ Digital Focus, which we conceptualize as a multidimensional construct that constitutes the volume, sentiment, and engagement of social media mentions and web search trends on Bitcoin prices, volatility, and growth. Specifically, we hypothesize that Tweet volumes (mentions), impressions, positive tweet sentiment, and engagement (immediate and lagged effect) for regular and verified users and internet search volume positively impact Bitcoin prices. We also hypothesize that Tweets with negative sentiment have a counter effect. Our study uses primary data from Blockchain, Twitter, and Google Search to test these hypotheses. Regression analysis finds broad support for our research model. Overall, we uncover novel insights that challenge conventional thinking regarding engagement and sentiment and present fresh insights into the influence of web searches and Twitter impressions on Bitcoin pricing.

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An Exploratory Analyses of Consumers’ Digital Focus on Bitcoin Price and Activity

  • B. Muralikrishnan,
  • Abhinav Mathur,
  • N. Govindrajan,
  • Anita Manda

摘要

Existing literature attempting to model the determinants of Bitcoin pricing has used a combination of economic, transactional, and technical factors as the independent variables. We seek to build on this body of knowledge by narrowing our investigation to the impact of Consumers’ Digital Focus, which we conceptualize as a multidimensional construct that constitutes the volume, sentiment, and engagement of social media mentions and web search trends on Bitcoin prices, volatility, and growth. Specifically, we hypothesize that Tweet volumes (mentions), impressions, positive tweet sentiment, and engagement (immediate and lagged effect) for regular and verified users and internet search volume positively impact Bitcoin prices. We also hypothesize that Tweets with negative sentiment have a counter effect. Our study uses primary data from Blockchain, Twitter, and Google Search to test these hypotheses. Regression analysis finds broad support for our research model. Overall, we uncover novel insights that challenge conventional thinking regarding engagement and sentiment and present fresh insights into the influence of web searches and Twitter impressions on Bitcoin pricing.